Optimising clinical care through CDH1-specific germline variant curation: improvement of clinical assertions and updated curation guidelines.

BACKGROUND: Germline pathogenic variants in CDH1 are associated with increased risk of diffuse gastric cancer and lobular breast cancer. Risk reduction strategies include consideration of prophylactic surgery, thereby making accurate interpretation of germline CDH1 variants critical for physicians deciding on these procedures. The Clinical Genome Resource (ClinGen) CDH1 Variant Curation Expert Panel (VCEP) developed specifications for CDH1 variant curation with a goal to resolve variants of uncertain significance (VUS) and with ClinVar conflicting interpretations and continues to update these specifications. METHODS: CDH1 variant classification specifications were modified based on updated genetic testing clinical criteria, new recommendations from ClinGen and expert knowledge from ongoing CDH1 variant curations. The CDH1 VCEP reviewed 273 variants using updated CDH1 specifications and incorporated published and unpublished data provided by diagnostic laboratories. RESULTS: Updated CDH1-specific interpretation guidelines include 11 major modifications since the initial specifications from 2018. Using the refined guidelines, 97% (36 of 37) of variants with ClinVar conflicting interpretations were resolved to benign, likely benign, likely pathogenic or pathogenic, and 35% (15 of 43) of VUS were resolved to benign or likely benign. Overall, 88% (239 of 273) of curated variants had non-VUS classifications. To date, variants classified as pathogenic are either nonsense, frameshift, splicing, or affecting the translation initiation codon, and the only missense variants classified as pathogenic or likely pathogenic have been shown to affect splicing. CONCLUSIONS: The development and evolution of CDH1-specific criteria by the expert panel resulted in decreased uncertain and conflicting interpretations of variants in this clinically actionable gene, which can ultimately lead to more effective clinical management recommendations.

Development and Validation of the Gene Expression Predictor of High-grade Serous Ovarian Carcinoma Molecular SubTYPE (PrOTYPE).

PURPOSE: Gene expression-based molecular subtypes of high-grade serous tubo-ovarian cancer (HGSOC), demonstrated across multiple studies, may provide improved stratification for molecularly targeted trials. However, evaluation of clinical utility has been hindered by nonstandardized methods, which are not applicable in a clinical setting. We sought to generate a clinical grade minimal gene set assay for classification of individual tumor specimens into HGSOC subtypes and confirm previously reported subtype-associated features. EXPERIMENTAL DESIGN: Adopting two independent approaches, we derived and internally validated algorithms for subtype prediction using published gene expression data from 1,650 tumors. We applied resulting models to NanoString data on 3,829 HGSOCs from the Ovarian Tumor Tissue Analysis consortium. We further developed, confirmed, and validated a reduced, minimal gene set predictor, with methods suitable for a single-patient setting. RESULTS: Gene expression data were used to derive the predictor of high-grade serous ovarian carcinoma molecular subtype (PrOTYPE) assay. We established a de facto standard as a consensus of two parallel approaches. PrOTYPE subtypes are significantly associated with age, stage, residual disease, tumor-infiltrating lymphocytes, and outcome. The locked-down clinical grade PrOTYPE test includes a model with 55 genes that predicted gene expression subtype with >95% accuracy that was maintained in all analytic and biological validations. CONCLUSIONS: We validated the PrOTYPE assay following the Institute of Medicine guidelines for the development of omics-based tests. This fully defined and locked-down clinical grade assay will enable trial design with molecular subtype stratification and allow for objective assessment of the predictive value of HGSOC molecular subtypes in precision medicine applications.See related commentary by McMullen et al., p. 5271.

CNspector: a web-based tool for visualisation and clinical diagnosis of copy number variation from next generation sequencing.

Next Generation Sequencing is now routinely used in the practice of diagnostic pathology to detect clinically relevant somatic and germline sequence variations in patient samples. However, clinical assessment of copy number variations (CNVs) and large-scale structural variations (SVs) is still challenging. While tools exist to estimate both, their results are typically presented separately in tables or static plots which can be difficult to read and are unable to show the context needed for clinical interpretation and reporting. We have addressed this problem with CNspector, a multi-scale interactive browser that shows CNVs in the context of other relevant genomic features to enable fast and effective clinical reporting. We illustrate the utility of CNspector at different genomic scales across a variety of sample types in a range of case studies. We show how CNspector can be used for diagnosis and reporting of exon-level deletions, focal gene-level amplifications, chromosome and chromosome arm level amplifications/deletions and in complex genomic rearrangements. CNspector is a web-based clinical variant browser tailored to the clinical application of next generation sequencing for CNV assessment. We have demonstrated the utility of this interactive software in typical applications across a range of tissue types and disease contexts encountered in the context of diagnostic pathology. CNspector is written in R and the source code is available for download under the GPL3 Licence from https://github.com/PapenfussLab/CNspector . A server running CNspector loaded with the figures from this paper can be accessed at https://shiny.wehi.edu.au/jmarkham/CNspector/index.html .

SDH-deficient renal cell carcinoma associated with biallelic mutation in succinate dehydrogenase A: comprehensive genetic profiling and its relation to therapy response.

Succinate dehydrogenase (SDH)-deficient renal cell carcinoma (RCC) is a rare RCC subtype that is caused by biallelic mutation of one of the four subunits of the SDH complex (SDHA, B, C, and D) and results in inactivation of the SDH enzyme. Here we describe a case of genetically characterized SDH-deficient RCC caused by biallelic (germline plus somatic) SDHA mutations. SDHA pathogenic variants were detected using comprehensive genomic profiling and SDH absence was subsequently confirmed by immunohistochemistry. Very little is known regarding the genomic context of SDH-deficient RCC. Interestingly we found genomic amplifications commonly observed in RCC but there was an absence of additional variants in common cancer driver genes. Prior to genetic testing a PD-1 inhibitor treatment was administered. However, following the genetic results a succession of tyrosine kinase inhibitors were administered as targeted treatment options and we highlight how the genetic results provide a rationale for their effectiveness. We also describe how the genetic results benefited the patient by empowering him to adopt dietary and lifestyle changes in accordance with knowledge of the mechanisms of SDH-related tumorigenesis.

Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses.

Variations in sample quality are frequently encountered in small RNA-sequencing experiments, and pose a major challenge in a differential expression analysis. Removal of high variation samples reduces noise, but at a cost of reducing power, thus limiting our ability to detect biologically meaningful changes. Similarly, retaining these samples in the analysis may not reveal any statistically significant changes due to the higher noise level. A compromise is to use all available data, but to down-weight the observations from more variable samples. We describe a statistical approach that facilitates this by modelling heterogeneity at both the sample and observational levels as part of the differential expression analysis. At the sample level this is achieved by fitting a log-linear variance model that includes common sample-specific or group-specific parameters that are shared between genes. The estimated sample variance factors are then converted to weights and combined with observational level weights obtained from the mean-variance relationship of the log-counts-per-million using 'voom'. A comprehensive analysis involving both simulations and experimental RNA-sequencing data demonstrates that this strategy leads to a universally more powerful analysis and fewer false discoveries when compared to conventional approaches. This methodology has wide application and is implemented in the open-source 'limma' package.

Whole-genome characterization of chemoresistant ovarian cancer.

Patients with high-grade serous ovarian cancer (HGSC) have experienced little improvement in overall survival, and standard treatment has not advanced beyond platinum-based combination chemotherapy, during the past 30 years. To understand the drivers of clinical phenotypes better, here we use whole-genome sequencing of tumour and germline DNA samples from 92 patients with primary refractory, resistant, sensitive and matched acquired resistant disease. We show that gene breakage commonly inactivates the tumour suppressors RB1, NF1, RAD51B and PTEN in HGSC, and contributes to acquired chemotherapy resistance. CCNE1 amplification was common in primary resistant and refractory disease. We observed several molecular events associated with acquired resistance, including multiple independent reversions of germline BRCA1 or BRCA2 mutations in individual patients, loss of BRCA1 promoter methylation, an alteration in molecular subtype, and recurrent promoter fusion associated with overexpression of the drug efflux pump MDR1.

Efficient molecular subtype classification of high-grade serous ovarian cancer.

High-grade serous carcinomas (HGSCs) account for approximately 70% of all epithelial ovarian cancers diagnosed. Using microarray gene expression profiling, we previously identified four molecular subtypes of HGSC: C1 (mesenchymal), C2 (immunoreactive), C4 (differentiated), and C5 (proliferative), which correlate with patient survival and have distinct biological features. Here, we describe molecular classification of HGSC based on a limited number of genes to allow cost-effective and high-throughput subtype analysis. We determined a minimal signature for accurate classification, including 39 differentially expressed and nine control genes from microarray experiments. Taqman-based (low-density arrays and Fluidigm), fluorescent oligonucleotides (Nanostring), and targeted RNA sequencing (Illumina) assays were then compared for their ability to correctly classify fresh and formalin-fixed, paraffin-embedded samples. All platforms achieved > 90% classification accuracy with RNA from fresh frozen samples. The Illumina and Nanostring assays were superior with fixed material. We found that the C1, C2, and C4 molecular subtypes were largely consistent across multiple surgical deposits from individual chemo-naive patients. In contrast, we observed substantial subtype heterogeneity in patients whose primary ovarian sample was classified as C5. The development of an efficient molecular classifier of HGSC should enable further biological characterization of molecular subtypes and the development of targeted clinical trials.

Immune response to RB1-regulated senescence limits radiation-induced osteosarcoma formation.

Ionizing radiation (IR) and germline mutations in the retinoblastoma tumor suppressor gene (RB1) are the strongest risk factors for developing osteosarcoma. Recapitulating the human predisposition, we found that Rb1+/- mice exhibited accelerated development of IR-induced osteosarcoma, with a latency of 39 weeks. Initial exposure of osteoblasts to carcinogenic doses of IR in vitro and in vivo induced RB1-dependent senescence and the expression of a panel of proteins known as senescence-associated secretory phenotype (SASP), dominated by IL-6. RB1 expression closely correlated with that of the SASP cassette in human osteosarcomas, and low expression of both RB1 and the SASP genes was associated with poor prognosis. In vivo, IL-6 was required for IR-induced senescence, which elicited NKT cell infiltration and a host inflammatory response. Mice lacking IL-6 or NKT cells had accelerated development of IR-induced osteosarcomas. These data elucidate an important link between senescence, which is a cell-autonomous tumor suppressor response, and the activation of host-dependent cancer immunosurveillance. Our findings indicate that overcoming the immune response to senescence is a rate-limiting step in the formation of IR-induced osteosarcoma.

Polycomb repressive complex 2 (PRC2) suppresses Eµ-myc lymphoma.

Deregulation of polycomb group complexes polycomb repressive complex 1 (PRC1) and 2 (PRC2) is associated with human cancers. Although inactivating mutations in PRC2-encoding genes EZH2, EED, and SUZ12 are present in T-cell acute lymphoblastic leukemia and in myeloid malignancies, gain-of-function mutations in EZH2 are frequently observed in B-cell lymphoma, implying disease-dependent effects of individual mutations. We show that, in contrast to PRC1, PRC2 is a tumor suppressor in Eµ-myc lymphomagenesis, because disease onset was accelerated by heterozygosity for Suz12 or by short hairpin RNA-mediated knockdown of Suz12 or Ezh2. Accelerated lymphomagenesis was associated with increased accumulation of B-lymphoid cells in the absence of effects on apoptosis or cell cycling. However, Suz12-deficient B-lymphoid progenitors exhibit enhanced serial clonogenicity. Thus, PRC2 normally restricts the self-renewal of B-lymphoid progenitors, the disruption of which contributes to lymphomagenesis. This finding provides new insight regarding the functional contribution of mutations in PRC2 in a range of leukemias.

Epigenetic regulator Smchd1 functions as a tumor suppressor.

SMCHD1 is an epigenetic modifier of gene expression that is critical to maintain X chromosome inactivation. Here, we show in mouse that genetic inactivation of Smchd1 accelerates tumorigenesis in male mice. Loss of Smchd1 in transformed mouse embryonic fibroblasts increased tumor growth upon transplantation into immunodeficient nude mice. In addition, loss of Smchd1 in Eµ-Myc transgenic mice that undergo lymphomagenesis reduced disease latency by 50% relative to control animals. In premalignant Eµ-Myc transgenic mice deficient in Smchd1, there was an increase in the number of pre-B cells in the periphery, likely accounting for the accelerated disease in these animals. Global gene expression profiling suggested that Smchd1 normally represses genes activated by MLL chimeric fusion proteins in leukemia, implying that Smchd1 loss may work through the same pathways as overexpressed MLL fusion proteins do in leukemia and lymphoma. Notably, we found that SMCHD1 is underexpressed in many types of human hematopoietic malignancy. Together, our observations collectively highlight a hitherto uncharacterized role for SMCHD1 as a candidate tumor suppressor gene in hematopoietic cancers.